Cell adhesion under flow is a dynamic process dependent on multiple physical and chemical factors. Computational modeling of the complex processes involved in cellular adhesion will further the understanding of disease processes, development of new drugs and drug delivery systems, and development of new clinical therapies. The proposed research will expand on a previously developed algorithm, termed multi particle adhesive dynamics (MAD) that fuses rigorous boundary element calculations of particulate flow with a stochastic model of specific receptor-ligand binding. The algorithm has been validated for in vitro systems, however questions remain: (1) How do cylindrical and branched in vivo vessel geometries affect cellular adhesion and particulate flow characteristics? (2) How does the particulate nature of blood affect mass transport? These questions will be answered through a combination of computational modeling and experimentation. We hypothesize that extending the MAD simulations to depict complex in vivo geometries, including cylindrical geometries and vessel branching, should more accurately predict the in vivo biomechanics of cell transport and dynamics of neutrophil adhesion during inflammation. Given the dependence of mass transport on flow properties, combining mass transport calculations with MAD can provide further insight into transport properties in vivo. The model will be validated experimentally by comparison with intravital microscopy of cellular flow in mouse skeletal muscle. This study is intended to further the understanding of adhesive behavior in vivo and to develop functional links between physical and chemical factors in the microcirculation. [unreadable] [unreadable]